Gulnar Mehdi

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This paper describes the outcomes of an ongoing collaboration between Siemens and the University of Oxford, with the goal of facilitating the design of ontologies and their deployment in applications. Ontologies are often used in industry to capture the conceptual information models underpinning applications. We start by describing the role that such models(More)
In this demo we present the SOMM system that resulted from an ongoing collaboration between Siemens and the University of Oxford. The goal of this collaboration is to facilitate design and management of ontologies that capture conceptual information models underpinning various industrial applications. SOMM supports engineers with little background on(More)
Massive data streams from sensors and devices are prominent form of industrial data generated during condition-monitoring and diagnosis of complex systems. Data analytics and reasoning has emerged as a vital tool to harness massive data sets, providing insights into historical and real-time system conditions; enhanced decision support, reliability and cost(More)
Motivation. Diagnostic systems play an important role in industry since they help to maximise equipment’s up-time and minimise its maintenance and operating costs [16]. In the energy sector companies like Siemens often rely on rule-based diagnostics to analyse power generating equipment by, e.g., testing newly deployed electricity generating gas turbines(More)
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